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  <div class="section" id="numpy-empty">
<h1>numpy.empty<a class="headerlink" href="#numpy-empty" title="Permalink to this headline">¶</a></h1>
<dl class="function">
<dt id="numpy.empty">
<code class="sig-prename descclassname">numpy.</code><code class="sig-name descname">empty</code><span class="sig-paren">(</span><em class="sig-param">shape</em>, <em class="sig-param">dtype=float</em>, <em class="sig-param">order='C'</em><span class="sig-paren">)</span><a class="headerlink" href="#numpy.empty" title="Permalink to this definition">¶</a></dt>
<dd><p>Return a new array of given shape and type, without initializing entries.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><dl class="simple">
<dt><strong>shape</strong><span class="classifier">int or tuple of int</span></dt><dd><p>Shape of the empty array, e.g., <code class="docutils literal notranslate"><span class="pre">(2,</span> <span class="pre">3)</span></code> or <code class="docutils literal notranslate"><span class="pre">2</span></code>.</p>
</dd>
<dt><strong>dtype</strong><span class="classifier">data-type, optional</span></dt><dd><p>Desired output data-type for the array, e.g, <code class="xref py py-obj docutils literal notranslate"><span class="pre">numpy.int8</span></code>. Default is
<code class="xref py py-obj docutils literal notranslate"><span class="pre">numpy.float64</span></code>.</p>
</dd>
<dt><strong>order</strong><span class="classifier">{‘C’, ‘F’}, optional, default: ‘C’</span></dt><dd><p>Whether to store multi-dimensional data in row-major
(C-style) or column-major (Fortran-style) order in
memory.</p>
</dd>
</dl>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><dl class="simple">
<dt><strong>out</strong><span class="classifier">ndarray</span></dt><dd><p>Array of uninitialized (arbitrary) data of the given shape, dtype, and
order.  Object arrays will be initialized to None.</p>
</dd>
</dl>
</dd>
</dl>
<div class="admonition seealso">
<p class="admonition-title">See also</p>
<dl class="simple">
<dt><a class="reference internal" href="numpy.empty_like.html#numpy.empty_like" title="numpy.empty_like"><code class="xref py py-obj docutils literal notranslate"><span class="pre">empty_like</span></code></a></dt><dd><p>Return an empty array with shape and type of input.</p>
</dd>
<dt><a class="reference internal" href="numpy.ones.html#numpy.ones" title="numpy.ones"><code class="xref py py-obj docutils literal notranslate"><span class="pre">ones</span></code></a></dt><dd><p>Return a new array setting values to one.</p>
</dd>
<dt><a class="reference internal" href="numpy.zeros.html#numpy.zeros" title="numpy.zeros"><code class="xref py py-obj docutils literal notranslate"><span class="pre">zeros</span></code></a></dt><dd><p>Return a new array setting values to zero.</p>
</dd>
<dt><a class="reference internal" href="numpy.full.html#numpy.full" title="numpy.full"><code class="xref py py-obj docutils literal notranslate"><span class="pre">full</span></code></a></dt><dd><p>Return a new array of given shape filled with value.</p>
</dd>
</dl>
</div>
<p class="rubric">Notes</p>
<p><a class="reference internal" href="#numpy.empty" title="numpy.empty"><code class="xref py py-obj docutils literal notranslate"><span class="pre">empty</span></code></a>, unlike <a class="reference internal" href="numpy.zeros.html#numpy.zeros" title="numpy.zeros"><code class="xref py py-obj docutils literal notranslate"><span class="pre">zeros</span></code></a>, does not set the array values to zero,
and may therefore be marginally faster.  On the other hand, it requires
the user to manually set all the values in the array, and should be
used with caution.</p>
<p class="rubric">Examples</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">np</span><span class="o">.</span><span class="n">empty</span><span class="p">([</span><span class="mi">2</span><span class="p">,</span> <span class="mi">2</span><span class="p">])</span>
<span class="go">array([[ -9.74499359e+001,   6.69583040e-309],</span>
<span class="go">       [  2.13182611e-314,   3.06959433e-309]])         #uninitialized</span>
</pre></div>
</div>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">np</span><span class="o">.</span><span class="n">empty</span><span class="p">([</span><span class="mi">2</span><span class="p">,</span> <span class="mi">2</span><span class="p">],</span> <span class="n">dtype</span><span class="o">=</span><span class="nb">int</span><span class="p">)</span>
<span class="go">array([[-1073741821, -1067949133],</span>
<span class="go">       [  496041986,    19249760]])                     #uninitialized</span>
</pre></div>
</div>
</dd></dl>

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